Machine learning approaches to power-system security assessment

The paper discusses a framework that uses machine learning and other automatic-learning methods to assess power-system security. The framework exploits simulation models in parallel to screen diverse simulation scenarios of a system, yielding a large database. Using data mining techniques, the framework extracts synthetic information about the simulated system's main features from this database.